Search results for: volumetric heat generation

Authors: M. Vezir Kahraman, Emre Basturk

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Energy storage technology offers new ways to meet the demand to obtain efficient and reliable energy storage materials. Thermal energy storage systems provide the potential to acquire energy savings, which in return decrease the environmental impact related to energy usage. For this purpose, phase change materials (PCMs) that work as 'latent heat storage units' which can store or release large amounts of energy are preferred. Phase change materials (PCMs) are being utilized to absorb, collect and discharge thermal energy during the cycle of melting and freezing, converting from one phase to another. Phase Change Materials (PCMs) can generally be arranged into three classes: organic materials, salt hydrates and eutectics. Many kinds of organic and inorganic PCMs and their blends have been examined as latent heat storage materials. PCMs have found different application areas such as solar energy storage and transfer, HVAC (Heating, Ventilating and Air Conditioning) systems, thermal comfort in vehicles, passive cooling, temperature controlled distributions, industrial waste heat recovery, under floor heating systems and modified fabrics in textiles. Ultraviolet (UV)-curing technology has many advantages, which made it applicable in many different fields. Low energy consumption, high speed, room-temperature operation, low processing costs, high chemical stability, and being environmental friendly are some of its main benefits. UV-curing technique has many applications. One of the many advantages of UV-cured PCMs is that they prevent the interior PCMs from leaking. Shape-stabilized PCM is prepared by blending the PCM with a supporting material, usually polymers. In our study, this problem is minimized by coating the fatty alcohols with a photo-cross-linked thiol-ene based polymeric system. Leakage is minimized because photo-cross-linked polymer acts a matrix. The aim of this study is to introduce a novel thiol-ene based shape-stabilized PCM. Photo-crosslinked thiol-ene based polymers containing fatty alcohols were prepared and characterized for the purpose of phase change materials (PCMs). Different types of fatty alcohols were used in order to investigate their properties as shape-stable PCMs. The structure of the PCMs was confirmed by ATR-FTIR techniques. The phase transition behaviors, thermal stability of the prepared photo-crosslinked PCMs were investigated by differential scanning calorimetry (DSC) and thermogravimetric analysis (TGA). This work was supported by Marmara University, Commission of Scientific Research Project.

Keywords: differential scanning calorimetry (DSC), Polymeric phase change material, thermal energy storage, UV-curing

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Authors: Biswajit Pal, Amit Mallik, Anil K. Barik

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Current years have witnessed a phenomenal growth in the research on the rare earth-doped transparent host materials, the essential components in optoelectronics that meet up the increasing demand for fabrication of high quality optical devices especially in telecommunication system. The combination of low phonon energy (because of fluoride environment) and high chemical durability with superior mechanical stability (due to oxide environment) makes the oxyfluoride glass–ceramics the promising and useful materials in optoelectronics. The present work reports on the undoped and doped (1 mol% Pr2O3) glass ceramics of composition 16.52 Al2O3•1.5AlF3• 12.65LaF3•4.33Na2O•64.85 SiO2 (mol%), prepared by melting technique initially that follows annealation at 450 ºC for 1 h. The glass samples so obtained were heat treated at constant 600 ºC with a variation in heat treatment schedule (10- 80 h). TEM techniques were employed to structurally characterize the glass samples. Pr2O3 affects the phase separation in the glass and delays the onset of crystallization in the glass ceramic. The modified crystallization mechanism is established from the analysis of advanced STEM/EDXS results. The phase separated droplets after annealing turn into 10-20 nm of LaF3 nano crystals those upon scrutiny are found to be dotted with the doped Pr3+ ions within the crystals themselves. The EDXS results also suggest that the inner LaF3 crystal core is swallowed by an Al enriched layer that follows a Si enriched surrounding shell as the outer core. This greatly increases the viscosity in the periphery of the crystals that restricts further crystal growth to account for the formation of nano sized crystals.

Keywords: advanced STEM/EDXS, crystallization mechanism, nano crystals, pr3+ ion doped glass and glass ceramic, structural characterization

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Authors: Marcello De Falco, Gianluca Natrella, Mauro Capocelli

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CO₂ capture and utilization (CCU) is a promising approach to reduce GHG(greenhouse gas) emissions. Many technologies in this field are recently attracting attention. However, since CO₂ is a very stable compound, its utilization as a reagent is energetic intensive. As a consequence, it is unclear whether CCU processes allow for a net reduction of environmental impacts from a life cycle perspective and whether these solutions are sustainable. Among the tools to apply for the quantification of the real environmental benefits of CCU technologies, exergy analysis is the most rigorous from a scientific point of view. The exergy of a system is the maximum obtainable work during a process that brings the system into equilibrium with its reference environment through a series of reversible processes in which the system can only interact with such an environment. In other words, exergy is an “opportunity for doing work” and, in real processes, it is destroyed by entropy generation. The exergy-based analysis is useful to evaluate the thermodynamic inefficiencies of processes, to understand and locate the main consumption of fuels or primary energy, to provide an instrument for comparison among different process configurations and to detect solutions to reduce the energy penalties of a process. In this work, the exergy analysis of a process for the production of Dimethyl Ether (DME) from green hydrogen generated through an electrolysis unit and pure CO₂ captured from flue gas is performed. The model simulates the behavior of all units composing the plant (electrolyzer, carbon capture section, DME synthesis reactor, purification step), with the scope to quantify the performance indices based on the II Law of Thermodynamics and to identify the entropy generation points. Then, a plant optimization strategy is proposed to maximize the exergy efficiency.

Keywords: green DME production, exergy analysis, energy penalties, exergy efficiency

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Authors: Minoo Ghasemzadeh, Rouzbeh Riazi, Shidvash Vakilipour, Alireza Ramezani

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In this study, thermo acoustic oscillations of a lean premixed combustor has been investigated, and a mono-dimensional code was developed in this regard. The linearized equations of motion are solved for perturbations with time dependence〖 e〗^iwt. Two flame models were considered in this paper and the effect of mean flow and boundary conditions were also investigated. After manipulation of flame heat release equation together with the equations of flow perturbation within the main components of the combustor model (i.e., plenum/ premixed duct/ and combustion chamber) and by considering proper boundary conditions between the components of model, a system of eight homogeneous equations can be obtained. This simplification, for the main components of the combustor model, is convenient since low frequency acoustic waves are not affected by bends. Moreover, some elements in the combustor are smaller than the wavelength of propagated acoustic perturbations. A convection time is also assumed to characterize the required time for the acoustic velocity fluctuations to travel from the point of injection to the location of flame front in the combustion chamber. The influence of an extended flame model on the acoustic frequencies of combustor was also investigated, assuming the effect of flame speed as a function of equivalence ratio perturbation, on the rate of flame heat release. The abovementioned system of equations has a related eigenvalue equation which has complex roots. The sign of imaginary part of these roots determines whether the disturbances grow or decay and the real part of these roots would give the frequency of the modes. The results show a reasonable agreement between the predicted values of dominant frequencies in the present model and those calculated in previous related studies.

Keywords: combustion instability, dominant frequencies, flame speed, premixed combustor

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Authors: Tatiana S. Ogneva

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Aluminum and nickel-based intermetallic compounds have attracted the attention of scientific community as promising materials for heat-resistant and wear-resistant coatings in such manufacturing areas as microelectronics, aircraft and rocket building and chemical industries. Magnetron sputtering makes possible to coat materials without formation of liquid phase and improves the mechanical and functional properties of nickel aluminides due to the possibility of nanoscale structure formation. The purpose of the study is the investigation of structure and properties of intermetallic coatings produced by magnetron sputtering technique. The feature of this work is the using of composite targets for sputtering, which were consisted of two semicircular sectors of cp-Ni and cp-Al. Plates of alumina, silicon, titanium and steel alloys were used as substrates. To estimate sputtering conditions on structure of intermetallic coatings, a series of samples were produced and studied in detail using scanning and transition electron microcopy and X-Ray diffraction. Besides, nanohardness and scratching tests were carried out. The varying parameters were the distance from the substrate to the target, the duration and the power of the sputtering. The thickness of the obtained intermetallic coatings varied from 0.05 to 0.5 mm depending on the sputtering conditions. The X-ray diffraction data indicated that the formation of intermetallic compounds occurred after sputtering without additional heat treatment. Sputtering at a distance not closer than 120 mm led to the formation of NiAl phase. Increase in the power of magnetron from 300 to 900 W promoted the increase of heterogeneity of the phase composition and the appearance of intermetallic phases NiAl, Ni₂Al₃, NiAl₃, and Al under the aluminum side, and NiAl, Ni₃Al, and Ni under the nickel side of the target. A similar trend is observed with increasing the distance of sputtering from 100 to 60 mm. The change in the phase composition correlates with the changing of the atomic composition of the coatings. Scanning electron microscopy revealed that the coatings have a nanoscale grain structure. In this case, the substrate material and the distance from the substrate to the magnetron have a significant effect on the structure formation process. The size of nanograins differs from 10 to 83 nm and depends not only on the sputtering modes but also on material of a substrate. Nanostructure of the material influences the level of mechanical properties. The highest level of nanohardness of the coatings deposited during 30 minutes on metallic substrates at a distance of 100 mm reached 12 GPa. It was shown that nanohardness depends on the grain size of the intermetallic compound. Scratching tests of the coatings showed a high level of adhesion of the coating to substrate without any delamination and cracking. The results of the study showed that magnetron sputtering of composite targets consisting of nickel and aluminum semicircles makes it possible to form intermetallic coatings with good mechanical properties directly in the process of sputtering without additional heat treatment.

Keywords: intermetallic coatings, magnetron sputtering, mechanical properties, structure

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Authors: Bruna C. Brasileiro, José Alberto S. Sá, Brigida R. P. Rocha

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The Amazon region development was related to large-scale projects associated with economic cycles. Economic cycles were originated from policies implemented by successive governments that exploited the resources and have not yet been able to improve the local population's quality of life. These implanted development strategies were based on vertical planning centered on State that didn’t know and showed no interest in know the local needs and potentialities. The future of this region is a challenge that depends on a model of development based on human progress associated to intelligent, selective and environmentally safe exploitation of natural resources settled in renewable and no-polluting energy generation sources – a differential factor of attraction of new investments in a context of global energy and environmental crisis. In this process the planning and support of Brazilian State, local government, and selective international partnership are essential. Residual biomass utilization allows the sustainable development by the integration of production chain and energy generation process which could improve employment condition and income of riversides. Therefore, this research discourses how the use of local residual biomass (açaí lumps) could be an important instrument of sustainable development for isolated communities located at Alcobaça Sustainable Development Reserve (SDR), Tucuruí, Pará State, since in this region the energy source more accessible for who can pay are the fossil fuels that reaches about 54% of final energy consumption by the integration between the açaí productive chain and the use of renewable energy source besides it can promote less environmental impact and decrease the use of fossil fuels and carbon dioxide emissions.

Keywords: Amazon, biomass, renewable energy, sustainability

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Authors: Geoffrey Sinha

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Today’s students are connected to the digital generation and technology is an integral part of their everyday lives. Clearly, this is one social revolution that is here to stay and the language classroom has been no exception. Furthermore, today’s teachers are also expected to connect with technology and online tools in their curriculum. However, it’s often difficult for teachers to know where to start, what resources and tools are available, what students should use, and most importantly, how to effectively use them in the classroom.

Keywords: language learning, new media, social media, technology

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Authors: Worawanna Panyakotkaew, Falan Srisuriyachai

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Cyclic steam injection (CSI) is a thermal recovery technique performed by injecting periodically heated steam into heavy oil reservoir. Oil viscosity is substantially reduced by means of heat transferred from steam. Together with gas pressurization, oil recovery is greatly improved. Nevertheless, prediction of effectiveness of the process is difficult when reservoir contains degree of heterogeneity. Therefore, study of heterogeneity together with interest reservoir properties must be evaluated prior to field implementation. In this study, thermal reservoir simulation program is utilized. Reservoir model is firstly constructed as multi-layered with coarsening upward sequence. The highest permeability is located on top layer with descending of permeability values in lower layers. Steam is injected from two wells located diagonally in quarter five-spot pattern. Heavy oil is produced by adjusting operating parameters including soaking period and steam quality. After selecting the best conditions for both parameters yielding the highest oil recovery, effects of degree of heterogeneity (represented by Lorenz coefficient), vertical permeability and permeability sequence are evaluated. Surprisingly, simulation results show that reservoir heterogeneity yields benefits on CSI technique. Increasing of reservoir heterogeneity impoverishes permeability distribution. High permeability contrast results in steam intruding in upper layers. Once temperature is cool down during back flow period, condense water percolates downward, resulting in high oil saturation on top layers. Gas saturation appears on top after while, causing better propagation of steam in the following cycle due to high compressibility of gas. Large steam chamber therefore covers most of the area in upper zone. Oil recovery reaches approximately 60% which is of about 20% higher than case of heterogeneous reservoir. Vertical permeability exhibits benefits on CSI. Expansion of steam chamber occurs within shorter time from upper to lower zone. For fining upward permeability sequence where permeability values are reversed from the previous case, steam does not override to top layers due to low permeability. Propagation of steam chamber occurs in middle of reservoir where permeability is high enough. Rate of oil recovery is slower compared to coarsening upward case due to lower permeability at the location where propagation of steam chamber occurs. Even CSI technique produces oil quite slowly in early cycles, once steam chamber is formed deep in the reservoir, heat is delivered to formation quickly in latter cycles. Since reservoir heterogeneity is unavoidable, a thorough understanding of its effect must be considered. This study shows that CSI technique might be one of the compatible solutions for highly heterogeneous reservoir. This competitive technique also shows benefit in terms of heat consumption as steam is injected periodically.

Keywords: cyclic steam injection, heterogeneity, reservoir simulation, thermal recovery

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Authors: Dawit Abay Tesfamariam

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Ethiopia’s Climate- Resilient Green Economy strategy focuses mainly on generating and utilization of Renewable Energy (RE). The data collected in 2016 by Ethiopian Electric Power (EEP) indicates that the intermittent RE sources on the grid from solar and wind energy were only 8 % of the total energy produced. On the other hand, the EEP electricity generation plan in 2030 indicates that 36 % of the energy generation share will be covered by solar and wind sources. Thus, a case study was initiated to model and compute the balance and consumption of electricity in three different scenarios: 2016, 2025, and 2030 using the Energy PLAN Model (EPM). Initially, the model was validated using the 2016 annual power-generated data to conduct the EPM analysis for two predictive scenarios. The EPM simulation analysis using EPM for 2016 showed that there was no significant excess power generated. Hence, the model’s results are in line with the actual 2016 output. Thus, the EPM was applied to analyze the role of energy storage in RE in Ethiopian grid systems. The results of the EPM simulation analysis showed there will be excess production of 402 /7963 MW average and maximum, respectively, in 2025. The excess power was dominant in all months except in the three rainy months of the year (June, July, and August). Consequently, based on the validated outcomes of EPM indicates, there is a good reason to think about other alternatives for the utilization of excess energy and storage of RE. Thus, from the scenarios and model results obtained, it is realistic to infer that; if the excess power is utilized with a storage mechanism that can stabilize the grid system; as a result, the extra RE generated can be exported to support the economy. Therefore, researchers must continue to upgrade the current and upcoming energy storage system to synchronize with RE potentials that can be generated from RE.

Keywords: renewable energy, storage, wind, energyplan

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Authors: Migael van Zyl, Stefanie Visser, Awelani Phaswana

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The electricity landscape in South Africa is characterized by frequent occurrences of loadshedding, a measure implemented by Eskom to manage electricity generation shortages by curtailing demand. Loadshedding, classified into stages ranging from 1 to 8 based on severity, involves the systematic rotation of power cuts across municipalities according to predefined schedules. However, this practice introduces distortions in recorded electricity demand, posing challenges to accurate forecasting essential for budgeting, network planning, and generation scheduling. Addressing this challenge requires the development of a methodology to quantify the impact of loadshedding and integrate it back into metered electricity demand data. Fortunately, comprehensive records of loadshedding impacts are maintained in a database, enabling the alignment of Loadshedding effects with hourly demand data. This adjustment ensures that forecasts accurately reflect true demand patterns, independent of loadshedding's influence, thereby enhancing the reliability of electricity supply management in South Africa. This paper presents a methodology for determining the hourly impact of load scheduling and subsequently adjusting historical demand data to account for it. Furthermore, two forecasting models are developed: one utilizing the original dataset and the other using the adjusted data. A comparative analysis is conducted to evaluate forecast accuracy improvements resulting from the adjustment process. By implementing this methodology, stakeholders can make more informed decisions regarding electricity infrastructure investments, resource allocation, and operational planning, contributing to the overall stability and efficiency of South Africa's electricity supply system.

Keywords: electricity demand forecasting, load shedding, demand side management, data science

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Authors: Angela Cristina Da F. De Oliveira, Salma E. Asmar, Norbert P. Battlori, Yaz Vera, Uriel R. Valencia, Tâmara Duarte Borges, Antoni D. Bueno, Leandro Batista Costa

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As homeothermic animals, pigs manifest maximum performance when kept at comfortable temperature levels, represented by a limit where thermoregulatory processes are minimal (18 - 20°C). In a stress situation where it will have a higher energy demand for thermal maintenance, the energy contribution to the productive functions will be reduced, generating health imbalances, drop in productive rates and welfare problems. The hypothesis of this project is that 5% starch replacement per 5% sunflower oil (SO), in growing and finishing pig’s diet (Iberic x Duroc), is effective as a nutritional strategy to reduce the negative impacts of thermal stress on performance and animal welfare. Seventy-two crossbred males (51± 6,29 kg body weight- BW) were housed according to the initial BW, in climate-controlled rooms, in collective pens, and exposed to heat stress conditions (30 - 32°C; 35% to 50% humidity). The experiment lasted 90 days, and it was carried out in a randomized block design, in a 2 x 2 factorial, composed of two diets (starch or sunflower oil (with or without) and two feed intake management (ad libitum and restriction). The treatments studied were: 1) control diet (5% starch x 0% SO) with ad libitum intake (n = 18); 2) SO diet (replacement of 5% of starch per 5% SO) with ad libitum intake (n = 18); 3) control diet with restriction feed intake (n = 18); or 4) SO diet with restriction feed intake (n = 18). Feed was provided in two phases, 50–100 Kg BW for growing and 100-140 Kg BW for finishing period, respectively. Hematological, biochemical and growth performance parameters were evaluated on all animals at the beginning of the environmental treatment, on the transition of feed (growing to finishing) and in the final of experiment. After the experimental period, when animals reached a live weight of 130-140 kg, they were slaughtered by carbon dioxide (CO2) stunning. Data have shown for the growing phase no statistical interaction between diet (control x SO) and management feed intake (ad libitum x restriction) on animal performance. At finishing phase, pigs fed with SO diet with restriction feed intake had the same average daily gain (ADG) compared with pigs in control diet with ad libitum feed intake. Furthermore, animals fed with the same diet (SO), presented a better feed gain (p < 0,05) due to feed intake reduce (p < 0,05) when compared with control group. To hematological and biochemical parameters, animals under heat stress had an increase in hematocrit, corpuscular volume, urea concentration, creatinine, calcium, alanine aminotransferase and aspartate aminotransferase (p < 0,05) when compared with the beginning of experiment. These parameters were efficient to characterize the heat stress, although the experimental treatments were not able to reduce the hematological and biochemical stress indicators. In addition, the inclusion of SO on pig diets improve feed gain in pigs at finishing phase, even with restriction feed intake.

Keywords: hematological, performance, pigs, welfare

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Authors: Nguyen Chi Quang, Nguyen Duong Tri Nguyen

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This article is the first step to research and outline the structure of the geotechnical database in the geological survey of a power project; in the context of this report creating the database that has been carried out for the Bac Ai pumped storage hydropower project. For the purpose of providing a method of organizing and storing geological and topographic survey data and experimental results in a spatial database, the RockWorks software is used to bring optimal efficiency in the process of exploiting, using, and analyzing data in service of the design work in the power engineering consulting. Three-dimensional (3D) geotechnical models are created from the survey data: such as stratigraphy, lithology, porosity, etc. The results of the 3D geotechnical model in the case of Bac Ai pumped storage hydropower project include six closely stacked stratigraphic formations by Horizons method, whereas modeling of engineering geological parameters is performed by geostatistical methods. The accuracy and reliability assessments are tested through error statistics, empirical evaluation, and expert methods. The three-dimensional model analysis allows better visualization of volumetric calculations, excavation and backfilling of the lake area, tunneling of power pipelines, and calculation of on-site construction material reserves. In general, the application of engineering geological modeling makes the design work more intuitive and comprehensive, helping construction designers better identify and offer the most optimal design solutions for the project. The database always ensures the update and synchronization, as well as enables 3D modeling of geological and topographic data to integrate with the designed data according to the building information modeling. This is also the base platform for BIM & GIS integration.

Keywords: database, engineering geology, 3D Model, RockWorks, Bac Ai pumped storage hydropower project

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Authors: Yang Shen, Yongpan Cheng, Jinliang Xu

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The effective blade cooling is of great significance for improving the performance of turbine. The mist cooling emerges as the promising way compared with the transitional single-phase cooling. In the mist cooling, the injected droplet will evaporate rapidly, and cool down the blade surface due to the absorbed latent heat, hence the lifetime for evaporating droplet becomes critical for design of cooling passages for the blade. So far there have been extensive studies on the droplet evaporation, but usually the isothermal model is applied for most of the studies. Actually the surface cooling effect can affect the droplet evaporation greatly, it can prolong the droplet evaporation lifetime significantly. In our study, a new theoretical model for sessile droplet evaporation with surface cooling effect is built up in toroidal coordinate. Three evaporation modes are analyzed during the evaporation lifetime, include “Constant Contact Radius”(CCR) mode、“Constant Contact Angle”(CCA) mode and “stick-slip”(SS) mode. The dimensionless number E0 is introduced to indicate the strength of the evaporative cooling, it is defined based on the thermal properties of the liquid and the atmosphere. Our model can predict accurately the lifetime of evaporation by validating with available experimental data. Then the temporal variation of droplet volume, contact angle and contact radius are presented under CCR, CCA and SS mode, the following conclusions are obtained. 1) The larger the dimensionless number E0, the longer the lifetime of three evaporation cases is; 2) The droplet volume over time still follows “2/3 power law” in the CCA mode, as in the isothermal model without the cooling effect; 3) In the “SS” mode, the large transition contact angle can reduce the evaporation time in CCR mode, and increase the time in CCA mode, the overall lifetime will be increased; 4) The correction factor for predicting instantaneous volume of the droplet is derived to predict the droplet life time accurately. These findings may be of great significance to explore the dynamics and heat transfer of sessile droplet evaporation.

Keywords: blade cooling, droplet evaporation, lifetime, theoretical analysis

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Authors: Utkarsh A. Mishra, Ankit Bansal

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At high temperature, radiative heat transfer is the dominant mode of heat transfer. It is governed by various phenomena such as photon emission, absorption, and scattering. The solution of the governing integrodifferential equation of radiative transfer is a complex process, more when the effect of participating medium and wavelength properties are taken into consideration. Although a generic formulation of such radiative transport problem can be modeled for a wide variety of problems with non-gray, non-diffusive surfaces, there is always a trade-off between simplicity and accuracy of the problem. Recently, solutions of complicated mathematical problems with statistical methods based on randomization of naturally occurring phenomena have gained significant importance. Photon bundles with discrete energy can be replicated with random numbers describing the emission, absorption, and scattering processes. Photon Monte Carlo (PMC) is a simple, yet powerful technique, to solve radiative transfer problems in complicated geometries with arbitrary participating medium. The method, on the one hand, increases the accuracy of estimation, and on the other hand, increases the computational cost. The participating media -generally a gas, such as CO₂, CO, and H₂O- present complex emission and absorption spectra. To model the emission/absorption accurately with random numbers requires a weighted sampling as different sections of the spectrum carries different importance. Importance sampling (IS) was implemented to sample random photon of arbitrary wavelength, and the sampled data provided unbiased training of MC estimators for better results. A better replacement to uniform random numbers is using deterministic, quasi-random sequences. Halton, Sobol, and Faure Low-Discrepancy Sequences are used in this study. They possess better space-filling performance than the uniform random number generator and gives rise to a low variance, stable Quasi-Monte Carlo (QMC) estimators with faster convergence. An optimal supervised learning scheme was further considered to reduce the computation costs of the PMC simulation. A one-dimensional plane-parallel slab problem with participating media was formulated. The history of some randomly sampled photon bundles is recorded to train an Artificial Neural Network (ANN), back-propagation model. The flux was calculated using the standard quasi PMC and was considered to be the training target. Results obtained with the proposed model for the one-dimensional problem are compared with the exact analytical and PMC model with the Line by Line (LBL) spectral model. The approximate variance obtained was around 3.14%. Results were analyzed with respect to time and the total flux in both cases. A significant reduction in variance as well a faster rate of convergence was observed in the case of the QMC method over the standard PMC method. However, the results obtained with the ANN method resulted in greater variance (around 25-28%) as compared to the other cases. There is a great scope of machine learning models to help in further reduction of computation cost once trained successfully. Multiple ways of selecting the input data as well as various architectures will be tried such that the concerned environment can be fully addressed to the ANN model. Better results can be achieved in this unexplored domain.

Keywords: radiative heat transfer, Monte Carlo Method, pseudo-random numbers, low discrepancy sequences, artificial neural networks

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Authors: J. Miranda, D. Chavarría-Barrientos, M. Ramírez-Cadena, M. E. Macías, P. Ponce, J. Noguez, R. Pérez-Rodríguez, P. K. Wright, A. Molina

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Higher education methods need to evolve because the new generations of students are learning in different ways. One way is by adopting emergent technologies, new learning methods and promoting the maker movement. As a result, Tecnologico de Monterrey is developing Open Innovation Laboratories as an immediate response to educational challenges of the world. This paper presents an Open Innovation Laboratory for Rapid Realization of Sensing, Smart and Sustainable Products (S³ Products). The Open Innovation Laboratory is composed of a set of specific resources where students and teachers use them to provide solutions to current problems of priority sectors through the development of a new generation of products. This new generation of products considers the concepts Sensing, Smart, and Sustainable. The Open Innovation Laboratory has been implemented in different courses in the context of New Product Development (NPD) and Integrated Manufacturing Systems (IMS) at Tecnologico de Monterrey. The implementation consists of adapting this Open Innovation Laboratory within the course’s syllabus in combination with the implementation of specific methodologies for product development, learning methods (Active Learning and Blended Learning using Massive Open Online Courses MOOCs) and rapid product realization platforms. Using the concepts proposed it is possible to demonstrate that students can propose innovative and sustainable products, and demonstrate how the learning process could be improved using technological resources applied in the higher educational sector. Finally, examples of innovative S³ products developed at Tecnologico de Monterrey are presented.

Keywords: active learning, blended learning, maker movement, new product development, open innovation laboratory

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Authors: Yu-Hsuan Chang, Jian-Hao Su, Chen-Yu Chen, Wei-Mon Yan

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In this work, the experimental measurement was applied to examine the membrane type and flow field design on the performance of a planar membrane humidifier. The performance indexes were used to evaluate the planar membrane humidifier. The performance indexes of the membrane humidifier include the dew point approach temperature (DPAT), water recovery ratio (WRR), water flux (J) and pressure loss (P). The experiments contain mainly three parts. In the first part, a single membrane humidifier was tested using different flow field under different dry-inlet temperatures. The measured results show that the dew point approach temperature decreases with increasing the depth of flow channel at the same width of flow channel. However, the WRR and J reduce with an increase in the dry air-inlet temperature. The pressure loss tests indicate that pressure loss decreases with increasing the hydraulic diameter of flow channel, resulting from an increase in Darcy friction. Owing to the comparison of humidifier performances and pressure losses, the flow channel of width W=1 and height H=1.5 was selected as the channel design of the multi-membrane humidifier in the second part of experiment. In the second part, the multi-membrane humidifier was used to evaluate the humidification performance under different relative humidity and flow rates. The measurement results indicate that the humidifier at both lower temperature and relative humidity of inlet dry air have higher DPAT but lower J and WRR. In addition, the counter flow approach has better mass and heat transfer performance than the parallel flow approach. Moreover, the effects of dry air temperature, relative humidity and humidification approach are not significant to the pressure loss in the planar membrane humidifier. For the third part, different membranes were tested in this work in order to find out which kind membrane is appropriate for humidifier.

Keywords: water management, planar membrane humidifier, heat and mass transfer, pressure loss, PEM fuel cell

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Authors: Muhammad Shahid, Kafait Ullah, Kashif Imran, Arshad Mahmood, Maarten Arentsen

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Poor planning and governance in the power sector of Pakistan have generated several issues ranging from gradual reliance on thermal-based expensive energy mix, supply shortages, unrestricted demand, subsidization, inefficiencies at different levels of the value chain and resultantly, the circular debt. This situation in the power sector has also hampered the growth of allied economic sectors. This study uses the Long-range Energy Alternative Planning (LEAP) system for electricity modelling of Pakistan from the period of 2016 to 2040. The study has first time in Pakistan forecasted the electricity demand at the provincial level. At the supply side, five scenarios Business as Usual Scenario (BAUS), Coal Scenario (CS), Gas Scenario (GS), Nuclear Scenario (NS) and Renewable Scenario (RS) have been analyzed based on the techno-economic and environmental parameters. The study has also included environmental externality costs for evaluating the actual costs and benefits of different scenarios. Contrary to the expectations, RS has a lower output than even BAUS. The study has concluded that the generation from RS has five times lesser costs than BAUS, CS, and GS. NS can also be an alternative for the sustainable future of Pakistan. Generation from imported coal is not a good option, however, indigenous coal with clean coal technologies should be promoted. This paper proposes energy planners of the country to devise incentives for the utilization of indigenous energy resources including renewables on priority and then clean coal to reduce the energy crises of Pakistan.

Keywords: economic evaluation, externality cost, penetration of renewable energy, regional electricity supply-demand planning

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Authors: Kristine Nore, Alexander Severnisen, Petter Arnestad, Dimitris Kraniotis, Roy Rossebø

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Natural materials like wood, absorb and release moisture. Thus wood can buffer indoor climate. When used wisely, this buffer potential can be used to counteract the outer climate influence on the building. The mass of moisture used in the buffer is defined as the potential hygrothermal mass, which can be an energy storage in a building. This works like a natural heat pump, where the moisture is active in damping the diurnal changes. In Norway, the ability of wood as a material used for climate buffering is tested in several buildings with the extensive use of wood, including supermarkets. This paper defines the potential of hygrothermal mass in a supermarket building. This includes the chosen ventilation strategy, and how the climate impact of the building is reduced. The building is located above the arctic circle, 50m from the coastline, in Valnesfjord. It was built in 2015, has a shopping area, including toilet and entrance, of 975 m². The climate of the area is polar according to the Köppen classification, but the supermarket still needs cooling on hot summer days. In order to contribute to the total energy balance, wood needs dynamic influence to activate its hygrothermal mass. Drying and moistening of the wood are energy intensive, and this energy potential can be exploited. Examples are to use solar heat for drying instead of heating the indoor air, and raw air with high enthalpy that allow dry wooden surfaces to absorb moisture and release latent heat. Weather forecasts are used to define the need for future cooling or heating. Thus, the potential energy buffering of the wood can be optimized with intelligent ventilation control. The ventilation control in Valnesfjord includes the weather forecast and historical data. That is a five-day forecast and a two-day history. This is to prevent adjustments to smaller weather changes. The ventilation control has three zones. During summer, the moisture is retained to dampen for solar radiation through drying. In the winter time, moist air let into the shopping area to contribute to the heating. When letting the temperature down during the night, the moisture absorbed in the wood slow down the cooling. The ventilation system is shut down during closing hours of the supermarket in this period. During the autumn and spring, a regime of either storing the moisture or drying out to according to the weather prognoses is defined. To ensure indoor climate quality, measurements of CO₂ and VOC overrule the low energy control if needed. Verified simulations of the Valnesfjord building will build a basic model for investigating wood as a climate regulating material also in other climates. Future knowledge on hygrothermal mass potential in materials is promising. When including the time-dependent buffer capacity of materials, building operators can achieve optimal efficiency of their ventilation systems. The use of wood as a climate regulating material, through its potential hygrothermal mass and connected to weather prognoses, may provide up to 25% energy savings related to heating, cooling, and ventilation of a building.

Keywords: climate buffer, energy, hygrothermal mass, ventilation, wood, weather forecast

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Authors: Bouchou Aïssa, Mohamed Akbi

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Contact materials used for electrical breakers are often made with silver alloys. Mechanical and thermo dynamical properties as well as electron emission of such complicated alloys present a lack of reliable and accurate experimental data. This paper deals mainly with electron work function (EWF) measurements about silver-metal oxide (Ag-MeO) electrical contacts (Ag-ZnO (92/8), before and after surface heat treatments at 296 K  813 K, under UHV conditions (residual gas pressure of 1.4 x 10-7 mbar). The electron work function (EWF) of silver zinc oxide materials was measured photoelectrically, using both Fowler’s method of isothermal curves and linearized Fowler plots. In this paper, we present the development of a method for measuring photoelectric work function of contact materials. Also reported in this manuscript are the results of experimental work whose purpose has been the buildup of a reliable photoelectric system and associated monochromatic ultra-violet radiations source, and the photoelectric measurement of the electron work functions (EWF) of contact materials. In order to study the influence of annealing temperature on the EWF, a vacuum furnace was used for heating the metallic samples up to 800 K. The EWF of the silver – zinc oxide materials were investigated to study the influence of annealing temperature on the EWF. In the present study, the photoelectric measurements about Ag-ZnO(92/8) contacts have shown a linear decrease of the EWF with increasing temperature, i.e. the temperature coefficient is constant and negative: for the first annealing # 1, in the temperature range [299 K  823 K]. On the contrary, a linear increase was observed with increasing temperature (i.e. , being constant and positive), for the next annealing # 2, in the temperature range [296 K  813 K]. The EWFs obtained for silver-zinc oxide Ag-ZnO(92/8) show an obvious dependence on the annealing temperature which is strongly associated with the evolution of the arrangement on ZnO nano particles on the Ag-ZnO contact surface as well as surface charge distribution.

Keywords: Photoemission, Electron work function, Fowler methods, Ag-ZnO contact materials, Vacuum heat treatment

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Authors: Parvin Goli, Amirhosein Kefayat, Rezvan Goli

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Background: It is well established that parents can influence their offspring's neurodevelopment. It is shown that paternal environment and lifestyle is beneficial for the progeny's fitness and might affect their metabolic mechanisms; however, the effects of paternal exercise on the brain in the offspring have not been explored in detail. Objective: This study aims to review the impact of paternal physical exercise on memory and learning, neuroplasticity, as well as DNA methylation levels in the off-spring's hippocampus. Study design: In this systematic review and meta-analysis, an electronic literature search was conducted in databases including PubMed, Scopus, and Web of Science. Eligible studies were those with an experimental design, including an exercise intervention arm, with the assessment of any type of memory function, learning ability, or any type of brain plasticity as the outcome measures. Standardized mean difference (SMD) and 95% confidence intervals (CI) were computed as effect size. Results: The systematic review revealed the important role of environmental enrichment in the behavioral development of the next generation. Also, offspring of exercised fathers displayed higher levels of memory ability and lower level of brain-derived neurotrophic factor. A significant effect of paternal exercise on the hippocampal volume was also reported in the few available studies. Conclusion: These results suggest an intergenerational effect of paternal physical activity on cognitive benefit, which may be associated with hippocampal epigenetic programming in offspring. However, the biological mechanisms of this modulation remain to be determined.

Keywords: hippocampal plasticity, learning ability, memory, parental exercise

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Authors: Shigenori Togashi, Yukako Asano

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We developed an effective microfluidic device for photoreactions with low reflectance and good heat conductance. The performance of this microfluidic device was tested by carrying out a photoreactive synthesis of benzopinacol and acetone from benzophenone and 2-propanol. The yield reached 36% with an irradiation time of 469.2 s and was improved by more than 30% when compared to the values obtained by the batch method. Therefore, the microfluidic device was found to be effective for improving the yields of photoreactions.

Keywords: microfluidic device, photoreaction, black aluminum oxide, benzophenone, yield improvement

Procedia PDF Downloads 243

Authors: Titin Handayani, Adi Mulyanto, Fajar Eko Priyanto

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It is generally recognized, that algae could be an interesting option for reducing CO₂ emissions. Based on light and CO₂, algae can be used for the production various economically interesting products. Current algae cultivation techniques, however, still present a number of limitations. Efficient feeding of CO₂, especially on a large scale, is one of them. Current methods for CO₂ feeding to algae cultures rely on the sparging pure CO₂ or directly from flue gas. The limiting factor in this system is the solubility of CO₂ in water, which demands a considerable amount of energy for an effective gas to liquid transfer and leads to losses to the atmosphere. Due to the current ineffective methods for CO₂ introduction into algae ponds very large surface areas would be required for enough ponds to capture a considerable amount of the CO₂. The purpose of this study is to assess technology to capture carbon dioxide (CO₂) emissions generated by industry by utilizing of microalgae Chlorella sp. The microalgae were cultivated in a bioreactor culture pond raceway type. The result is expected to be useful in mitigating the effects of greenhouse gases in reducing the CO₂ emissions. The research activities include: (1) Characterization of boiler flue gas, (2) Operation of culture pond, (3) Sampling and sample analysis. The results of this study showed that the initial assessment absorption of the flue gas by microalgae using 1000 L raceway pond completed by heat exchanger were quite promising. The transfer of CO₂ into the pond culture system was run well. This identified from the success of cooling the boiler flue gas from the temperature of about 200 °C to below ambient temperature. Except for the temperature, the gas bubbles into the culture media were quite fine. Therefore, the contact between the gas and the media was well performed. The efficiency of CO₂ absorption by Chlorella sp reached 6.68 % with an average CO₂ loading of 0.29 g/L/day.

Keywords: Chlorella sp., CO2 emission, heat exchange, microalgae, milk industry, raceway pond

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Authors: Pablo Oteiza, Ricardo Alvarez, Mehrdad Pirnia, Fuat Can

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To effectively combat climate change, many countries around the world have committed to a decarbonisation of their electricity, along with promoting a large-scale integration of renewable energy sources (RES). While this trend represents a unique opportunity to effectively combat climate change, achieving a sound and cost-efficient energy transition towards low-carbon power systems poses significant challenges for the multi-year Transmission Network Expansion Planning (TNEP) problem. The objective of the multi-year TNEP is to determine the necessary network infrastructure to supply the projected demand in a cost-efficient way, considering the evolution of the new generation mix, including the integration of RES. The rapid integration of large-scale RES increases the variability and uncertainty in the power system operation, which in turn increases short-term flexibility requirements. To meet these requirements, flexible generating technologies such as energy storage systems must be considered within the TNEP as well, along with proper models for capturing the operational challenges of future power systems. As a consequence, TNEP formulations are becoming more complex and difficult to solve, especially for its application in realistic-sized power system models. To meet these challenges, there is an increasing need for developing efficient algorithms capable of solving the TNEP problem with reasonable computational time and resources. In this regard, a promising research area is the use of artificial intelligence (AI) techniques for solving large-scale mixed-integer optimization problems, such as the TNEP. In particular, the use of AI along with mathematical optimization strategies based on decomposition has shown great potential. In this context, this paper presents an efficient algorithm for solving the multi-year TNEP problem. The algorithm combines AI techniques with Column Generation, a traditional decomposition-based mathematical optimization method. One of the challenges of using Column Generation for solving the TNEP problem is that the subproblems are of mixed-integer nature, and therefore solving them requires significant amounts of time and resources. Hence, in this proposal we solve a linearly relaxed version of the subproblems, and trained a binary classifier that determines the value of the binary variables, based on the results obtained from the linearized version. A key feature of the proposal is that we integrate the binary classifier into the optimization algorithm in such a way that the optimality of the solution can be guaranteed. The results of a study case based on the HRP 38-bus test system shows that the binary classifier has an accuracy above 97% for estimating the value of the binary variables. Since the linearly relaxed version of the subproblems can be solved with significantly less time than the integer programming counterpart, the integration of the binary classifier into the Column Generation algorithm allowed us to reduce the computational time required for solving the problem by 50%. The final version of this paper will contain a detailed description of the proposed algorithm, the AI-based binary classifier technique and its integration into the CG algorithm. To demonstrate the capabilities of the proposal, we evaluate the algorithm in case studies with different scenarios, as well as in other power system models.

Keywords: integer optimization, machine learning, mathematical decomposition, transmission planning

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Authors: Avinash Chaudhary, Akhilesh Gupta, Surendra Kumar, Ravi Kumar

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This paper presents the numerical study on Jatropha oil pool fire in a compartment. A fire experiment with jatropha oil was conducted in a compartment of size 4 m x 4 m x m to study the fire development and temperature distribution. Fuel is burned in the center of the compartment in a pool diameter of 0.5 m with an initial fuel depth of 0.045 m. Corner temperature in the compartment, doorway temperature and hot gas layer temperature at various locations are measured. Numerical simulations were carried out using Fire Dynamics Simulator (FDS) software at grid size of 0.05 m, 0.12 m and for performing simulation heat release rate of jatropha oil measured using mass loss method were inputted into FDS. Experimental results shows that like other fuel fires, the whole combustion process can be divided into four stages: initial stage, growth stage, steady profile or developed phase and decay stage. The fire behavior shows two zone profile where upper zone consists of mainly hot gases while lower zone is relatively at colder side. In this study, predicted temperatures from simulation are in good agreement in upper zone of compartment. Near the interface of hot and cold zone, deviations were reported between the simulated and experimental results which is probably due to the difference between the predictions of smoke layer height by FDS. Also, changing the grid size from 0.12 m to 0.05 m does not show any effect in temperatures at upper zone while in lower zone, grid size of 0.05 m showed satisfactory agreement with experimental results. Numerical results showed that calculated temperatures at various locations matched well with the experimental results. On the whole, an effective method is provided with reasonable results to study the burning characteristics of jatropha oil with numerical simulations.

Keywords: jatropha oil, compartment fire, heat release rate, FDS (fire dynamics simulator), numerical simulation

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Authors: Paul Lemarignier, Olivier Fiquet, Vincent Pateloup

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In line with the strong desire of nuclear energy players to have ever more effective products in terms of safety, research programs on E-ATF (Enhanced-Accident Tolerant Fuels) that are more resilient, particularly to the loss of coolant, have been launched in all countries with nuclear power plants. Among the multitude of solutions being developed internationally, carcinoembryonic antigen (CEA) and its partners are investigating a promising solution, which is the realization of CERMET (CERamic-METal) type fuel pellets made of a matrix of fissile material, uranium dioxide UO2, which has a low thermal conductivity, and a metallic phase with a high thermal conductivity to improve heat evacuation. Work has focused on the development by powder metallurgy of micro-structured CERMETs, characterized by networks of metallic phase embedded in the UO₂ matrix. Other types of macro-structured CERMETs, based on concepts proposed by thermal simulation studies, have been developed with a metallic phase with a specific geometry to optimize heat evacuation. This solution could not be developed using traditional processes, so additive manufacturing, which revolutionizes traditional design principles, is used to produce these innovative prototype concepts. At CEA Cadarache, work is first carried out on a non-radioactive surrogate material, alumina, in order to acquire skills and to develop the equipment, in particular the robocasting machine, an additive manufacturing technique selected for its simplicity and the possibility of optimizing the paste formulations. A manufacturing chain was set up, with the pastes production, the 3D printing of pellets, and the associated thermal post-treatment. The work leading to the first elaborations of macro-structured alumina/molybdenum CERMETs will be presented. This work was carried out with the support of Framatome and EdF.

Keywords: additive manufacturing, alumina, CERMET, molybdenum, nuclear safety

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Authors: Kamaljeet Kaur, Vinod Kumari, Jatesh Kathpalia, Bas Kaur

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A gender bias towards girl child is pervasive across the world. It is seen in all the strata of the society and manifests in various forms. However nature and extent of these inequalities are not uniform. Generally these inequalities are more prevalent in patriarchal society. Despite emerging and increasing opportunities for women, there are still inequalities between men and women in each and every sphere like education, health, economy, polity and social sphere. Patriarchal ideology as a cultural norm enforces gender construction which is oriented toward hierarchical relations between the sexes and neglect of women in Indian society. Discrimination to girls may also vary by their age and be restricted to the birth order and sex composition of her elder surviving siblings. The present study was conducted to know the gender discrimination among rural children in India. The respondents were selected from three generations as per AICRP age group viz, 18-30 years (3rd generation), 31-60 years (2nd generation) and above 60 years (1st generation). A total sample size was 600 respondents from different villages of two districts of Haryana state comprising of half males and half females. Data were collected using personal interview schedule and analysed by SPSS software. Among the total births 46.35 per cent were girl child and 53.64 % were male child. Dropout rate was more in female children as compared to male children i.e. near about one third (31.09%) female children dropped school followed by 21.17 % male children. It was quite surprising that near about two-third (61.16%) female children and more than half (59.22%) of the male children dropped school. Cooking was mainly performed by adult female with overall mean scores 2.0 and ranked first which was followed by female child (1.7 mean scores) clearly indicating that cooking was the activity performed mainly by females while activity related to purchase of fruits and vegetable, cereals and pulses was mainly done by adult male. First preference was given to male child for serving of costly and special food. Regarding professional aspiration of children of the respondents’ families, it was observed that 20.10% of the male children wanted to become engineer, whereas only 3.89 % female children wanted to become engineer. Ratio of male children was high in both generations irrespective of the districts. School dropouts were more in case of female in both the 1st and 2 nd generations. The main reasons of school dropout were lack of interest, lack of resources and early marriage in both the generations. Female enrolment was more in faculty of arts, whereas in case of male percentage it was more in faculty of non-medical and medical which showed that female children were getting traditional type of education. It is suggested to provide equal opportunities to girls and boys in home as well as outside the home for smooth functioning of society.

Keywords: gender biasness, male child, female child, education, home

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Authors: Ahmed Hossam ElMolla, Mohamed Hatem Saleh, Hamza Mostafa, Lara Mamdouh, Yassin Wael

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Artificial intelligence (AI) is reshaping industries, and its potential to revolutionize renewable energy and data center operations is immense. By harnessing AI's capabilities, we can optimize energy consumption, predict fluctuations in renewable energy generation, and improve the efficiency of data center infrastructure. This convergence of technologies promises a future where energy is managed more intelligently, sustainably, and cost-effectively. The integration of AI into renewable energy systems unlocks a wealth of opportunities. Machine learning algorithms can analyze vast amounts of data to forecast weather patterns, solar irradiance, and wind speeds, enabling more accurate energy production planning. AI-powered systems can optimize energy storage and grid management, ensuring a stable power supply even during intermittent renewable generation. Moreover, AI can identify maintenance needs for renewable energy infrastructure, preventing costly breakdowns and maximizing system lifespan. Data centers, which consume substantial amounts of energy, are prime candidates for AI-driven optimization. AI can analyze energy consumption patterns, identify inefficiencies, and recommend adjustments to cooling systems, server utilization, and power distribution. Predictive maintenance using AI can prevent equipment failures, reducing energy waste and downtime. Additionally, AI can optimize data placement and retrieval, minimizing energy consumption associated with data transfer. As AI transforms renewable energy and data center operations, modified Key Performance Indicators (KPIs) will emerge. Traditional metrics like energy efficiency and cost-per-megawatt-hour will continue to be relevant, but additional KPIs focused on AI's impact will be essential. These might include AI-driven cost savings, predictive accuracy of energy generation and consumption, and the reduction of carbon emissions attributed to AI-optimized operations. By tracking these KPIs, organizations can measure the success of their AI initiatives and identify areas for improvement. Ultimately, the synergy between AI, renewable energy, and data centers holds the potential to create a more sustainable and resilient future. By embracing these technologies, we can build smarter, greener, and more efficient systems that benefit both the environment and the economy.

Keywords: data center, artificial intelligence, renewable energy, energy efficiency, sustainability, optimization, predictive analytics, energy consumption, energy storage, grid management, data center optimization, key performance indicators, carbon emissions, resiliency

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Authors: D. Amaranatha Reddy

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Highly efficient and stable co-catalysts materials is of great important for boosting photo charge carrier’s separation, transportation efficiency, and accelerating the catalytic reactive sites of semiconductor photocatalysts. As a result, it is of decisive importance to fabricate low price noble metal free co-catalysts with high catalytic reactivity, but it remains very challenging. Considering this challenge here, dual metal organic frame work derived N-Doped Fe3C nanocages have been rationally designed and decorated with ultrathin ZnIn2S4 nanosheets for efficient photocatalytic hydrogen generation. The fabrication strategy precisely integrates co-catalyst nanocages with ultrathin two-dimensional (2D) semiconductor nanosheets by providing tightly interconnected nano-junctions and helps to suppress the charge carrier’s recombination rate. Furthermore, constructed highly porous hybrid structures expose ample active sites for catalytic reduction reactions and harvest visible light more effectively by light scattering. As a result, fabricated nanostructures exhibit superior solar driven hydrogen evolution rate (9600 µmol/g/h) with an apparent quantum efficiency of 3.6 %, which is relatively higher than the Pt noble metal co-catalyst systems and earlier reported ZnIn2S4 based nanohybrids. We believe that the present work promotes the application of sulfide based nanostructures in solar driven hydrogen production.

Keywords: photocatalysis, water splitting, hydrogen fuel production, solar-driven hydrogen

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Authors: Timo Miebach, Kirsten Hoeper, Carolin Felix

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In times of competitive pressures and demographic change, hospitals have to reconsider their strategies as a company. Due to the fact, that operations are one of the main income and one of the primary cost drivers otherwise, a process-oriented approach and an efficient use of resources seems to be the right way for getting a consistent market position. Thus, the efficient operation room occupancy planning is an important cause variable for the success and continued the existence of these institutions. A high utilization of resources is essential. This means a very high, but nevertheless sensible capacity-oriented utilization of working systems that can be realized by avoiding downtimes and a thoughtful occupancy planning. This engineering approach should help hospitals to reach her break-even point. Firstly, the aim is to establish a strategy point, which can be used for the generation of a planned throughput time. Secondly, the operation planning and control should be facilitated and implemented accurately by the generation of time modules. More than 100,000 data records of the Hannover Medical School were analyzed. The data records contain information about the type of conducted operation, the duration of the individual process steps, and all other organizational-specific data such as an operating room. Based on the aforementioned data base, a generally valid model was developed by an analysis to define a strategy point which takes the conflict of capacity utilization and low overtime into account. Furthermore, time modules were generated in this work, which allows a simplified and flexible operation planning and control for the operation manager. By the time modules, it is possible to reduce a high average value of the idle times of the operation rooms. Furthermore, the potential is used to minimize the idle time spread.

Keywords: capacity, operating room, surgery planning and control, utilization

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Authors: Eric Muñoz de la Torre, Julián González Trinidad, Efrén González Ramírez

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Rain varies greatly in its duration, intensity, and spatial coverage, it is important to have sub-daily rainfall data for various applications, including risk prevention. However, the ground measurements are limited by the low and irregular density of rain gauges. An alternative to this problem are the Satellite Precipitation Products (SPPs) that use passive microwave and infrared sensors to estimate rainfall, as IMERG, however, these SPPs have to be validated before their application. The aim of this study is to evaluate the performance of the IMERG: Integrated Multi-satellitE Retrievals for Global Precipitation Measurament final run V06B SPP in a semi-arid region of Mexico, using 4 automatic rain gauges (pluviographs) sub-daily data of October 2019 and June to September 2021, using the Minimum inter-event Time (MIT) criterion to separate unique rain events with a dry period of 10 hrs. for the purpose of evaluating the rainfall properties (depth, duration and intensity). Point to pixel analysis, continuous, categorical, and volumetric statistical metrics were used. Results show that IMERG is capable to estimate the rainfall depth with a slight overestimation but is unable to identify the real duration and intensity of the rain events, showing large overestimations and underestimations, respectively. The study zone presented 80 to 85 % of convective rain events, the rest were stratiform rain events, classified by the depth magnitude variation of IMERG pixels and pluviographs. IMERG showed poorer performance at detecting the first ones but had a good performance at estimating stratiform rain events that are originated by Cold Fronts.

Keywords: IMERG, rainfall, rain gauge, remote sensing, statistical evaluation

Procedia PDF Downloads 71